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[docs] document how to support operators with several vector arguments #3577

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Nov 22, 2023
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[docs] document how to support operators with several vector arguments #3577

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[docs] document how to support operators with several vector arguments
odow Nov 20, 2023
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Update docs/src/manual/nonlinear.md
odow Nov 21, 2023
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16 changes: 16 additions & 0 deletions docs/src/manual/nonlinear.md
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Expand Up @@ -556,6 +556,22 @@ f(x::Vector) = sum(x[i]^i for i in 1:length(x))
@objective(model, Min, op_f(x...))
```

If the operator takes several vector inputs, write a function which takes the
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splatted arguments and reconstructs the required vector inputs:
```@repl
using JuMP
model = Model();
@variable(model, x[1:2]);
@variable(model, y[1:2]);
@variable(model, z);
f(x::Vector, y::Vector, z) = sum((x[i] * y[i])^z for i in 1:2)
f(x, y, z)
f_splat(args...) = f(collect(args[1:2]), collect(args[3:4]), args[5])
f_splat(x..., y..., z)
@operator(model, op_f, 5, f_splat)
@objective(model, Min, op_f(x..., y..., z))
```

### Automatic differentiation

JuMP does not support black-box optimization, so all user-defined operators must
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